Periodicity and dissipativity for memristor-based mixed time-varying delayed neural networks via differential inclusions

New results on synchronization control of delayed memristive neural networks

“…And the proposed results here are different from the present works [7][8][9][10][11][12][13][14][15][16][17][18][19], and our results achieved a valuable improvement, and they also extend the earlier publications. The proposed method in this paper can be applied to study other dynamical behaviors of memristive neural networks, such as (1) periodicity and stability of memristive neural networks and (2) design the proper response system of memristive neural networks and then discuss anti-synchronization for the memristive neural networks.…”

“…1 can depict the simplification of memductance of the memristor. Basing on the previous works [7][8][9][10][11][12][13][14][15], in this paper, as the special …”

“…Recently, dynamic analysis of memristive neural networks has been attracted increasing attention; e.g., some sufficient conditions were obtained for stability or periodic solution [7][8][9][10][11][12][13], synchronization [14][15][16], dissipativity and attractivity [17][18][19].…”

“…The memristive neural network is a class of statedependent nonlinear systems from a systems-theoretic point of view [7][8][9][10][11][12][13][14][15][16][17][18][19]. Such system can reveal coexisting solutions, jumped, transient chaos of rich and complex nonlinear behaviors [14,16], and these problems bring challenges to investigate the exponential synchronization of such system.…”

Existence and global exponential stability of almost periodic solution for delayed competitive neural networks with discontinuous activations

“…In recent years, various neural networks such as cellular neural networks, Hopfield neural networks, bidirectional associative memory neural networks, and Cohen-Grossberg neural networks with discontinuous right-hand sides have been extensively investigated in both theory and application, and they have been successfully applied to signal processing, pattern recognition, associative memory, and optimization problems (see [1][2][3][4][5][6][7][8][9][10][11][12][13][14] and the references therein). Many results of these in-depth research mainly focused on the dynamics of the equilibrium point or periodic solution.…”